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How to add rows to a mtrix following a certain condition?
Suppose the following matrix r= [0; 1; 1.5; 1.6; 2; 10.4; 15.5]. How to add rows which are in the interval floor(r):0.1:floor...
대략 8년 전 | 답변 수: 2 | 0
2
답변답변 있음
How to add rows to a mtrix following a certain condition?
I found the problem. r=unique(r, 'rows', 'stable'); for i=1:size(r,1); p(i,:) = floor(r(i)):0.1:floor(r(i))+1; end q = ...
How to add rows to a mtrix following a certain condition?
I found the problem. r=unique(r, 'rows', 'stable'); for i=1:size(r,1); p(i,:) = floor(r(i)):0.1:floor(r(i))+1; end q = ...
대략 8년 전 | 0
질문
How to divide large data in small intervals?
How to divide a large matrix into small intervals? For example, take the matrix [1 1; 1 2; 2 3; ...;5 100; 6 100; ...; 1 1....
8년 초과 전 | 답변 수: 2 | 0
2
답변질문
How to reduce this matrix?
How to reduce this matrix? Suppose that M=[1 0.1 1.1; 1 0.1 1.1; 3 0.1 1.2; 2 0.2 3; 1 2 4; 2 2 4; 2 3 5]; based on the se...
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
How does the Box-Cox Transformation in Matlab work?
What is the explicitly Log-Likelihood Function (LLF) maximized? Are the variance and mean values computed from the data?
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
Does Matlab has relative square error available in Neural Network toolbox?
I have seen that MSE, SSE, MAE and SAE are possible training functions of a neural network in Matlab. Does it have relative squa...
8년 초과 전 | 답변 수: 2 | 0
2
답변질문
Is good to repeat the same sample in the training of the neural network?
Does the neural network improve repeating the same samples values during training?
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
Are there features that the input and target values should follow before training in a neural network?
Even with normalization or mapping in a range [-1,1] before training, I have seen that a good scaling of the data may improve th...
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
How to define error weights in Neural Network?
I want to minimize a mean squared weighted deviation in a neural network. The weights are different for each sample. How can ...
8년 초과 전 | 답변 수: 2 | 0
2
답변질문
Is the mse of the testing set in the neural network computed simultaneously with the mse of the training and validation sets?
In the performance plot, there are three curves: training, validation, testing. Is the mse of the testing set computed simultane...
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
Is possible to normalize just the training data instead of the whole data using Neural Network toolbox?
Using the Matlab functions, it is possible to normalize the input and output data that will feed the Neural Network. However, is...
8년 초과 전 | 답변 수: 2 | 0
2
답변질문
When I generate a Matlab function of a neural network, it comes with the normalization/re-normalization constants. Will these constants affect the neural network performance on another data set? Why?
The normalization/re-normalization (for example, mapping the data to [-1,1] or [0,1]) is built for the training data. What does ...
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
Neural Network in loops: How can I set up a loop to train at least 10 neural networks with the same parameters and save only the best performance, regression and histogram error, and the matrix-only MATLAB function for neural network code?
Hi, How can I set up a loop to train at least 10 neural networks with the same parameters and save only the best perform...
8년 초과 전 | 답변 수: 2 | 0
2
답변질문
Neural Network: what does mean when the R-value is close to 1, but MSE (mean squared error) is large?
Hi, Considering a trained neural network, what does mean when the R-value is close to 1, but MSE (mean squared error) is l...
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
Neural Network - net.divideFcn = 'divideind'
Hi, I am trying to use "net.divideFcn = 'divideind'". In my case, I want to merge two different range of indices, e.g., ...
8년 초과 전 | 답변 수: 1 | 0
1
답변질문
How can put eigenvalues in ascending order?
Hi, I am using something like [V,D] = eig(S) and I would like the eigenvalues in ascending order in the diagonal. V, D and S ...
거의 10년 전 | 답변 수: 1 | 0
1
답변질문
How can I make my loop works?
How can I make my loop works? I know P0 (my initial guess) P0 = 3.5378 -2.3325 -2.3325 3.5378 X = ...
거의 10년 전 | 답변 수: 1 | 0